The explosion of information available over network-based systems such as the Internet can overwhelm a person attempting to locate a desired piece of information or product. For example, the categories of products available through a typical network-based commerce system have grown exponentially over the last decade. This dramatic growth has left users with the problem of sorting and browsing through enormous amounts of data to find information or products relevant to their needs. Search engines and recommendation systems have both been developed to assist in locating both information and products within network-based systems.
Traditional recommendation systems have been implemented to attempt to assist users in locating relevant information or products. A successful recommendation system on a network-based commerce system not only saves users time in locating relevant products but also brings extra profits to the commerce system's operators. Most traditional recommendation systems utilize some form of searching technique. For example, traditional recommendation systems may access or otherwise obtain inventory data provided by merchants. The inventory data may indicate that a particular merchant (e.g., such as Best Buy®) may offer a given product for sale. Accordingly, such traditional recommendation systems rely on merchants to provide updates on what products are offered for sale. Often times, the inventory data provided by a merchant merely indicates that a merchant in general offers, or at some point had offered, a given product for sale.